Advancing health science research, education, and practice by turning data into knowledge and addressing the greatest public health issues of the 21st century.
The Department of Biostatistics at the Harvard Chan School offers an unparalleled environment to pursue research and education in statistical science while being at the forefront of efforts to benefit the health of populations worldwide.
- Our faculty are leaders in the development of statistical methods for clinical trials and observational studies, studies on the environment, and genomics/genetics
- Our graduates are armed with exceptional analytic and computing skills and are thriving in a wide range of careers in academia, industry, the government, and beyond
- Our innovative approaches to computational biology, quantitative genomics and the analysis of massive data are strengthened by a deep foundation in theory and application
- Our unique community provides countless resources and collaborative opportunities within Harvard Medical School, the Dana-Farber Cancer Institute and world-class hospitals in Boston
Watch one student’s inspiring story of what led them to study Biostatistics at Harvard.
Learn more about our pioneering research and our community of leading scientists, educators & students.
向日葵app破解版污 Copyright":"","focal_length":"50","iso":"800","shutter_speed":"0.02","title":"","orientation":"0"}" data-image-title="DSC_5101" data-image-description="" data-medium-file="https://cdn1.sph.harvard.edu/wp-content/uploads/sites/59/2012/09/DSC_5101-300x200.jpg" data-large-file="https://cdn1.sph.harvard.edu/wp-content/uploads/sites/59/2012/09/DSC_5101-1024x683.jpg" class="alignleft size-full wp-image-3209" src="static/picture/DSC_5101-e1461082174842.jpg" alt="含羞草实验研究所app破解版污" width="200" height="143">Academics
Our programs provide students with a rigorous training in statistical theory, methods, and computation—and to use what they learn in the classroom to address real-world problems in public health.
Our Faculty work with researchers both locally and globally to apply statistical and computational methods to HIV and infectious disease research, chronic diseases, environmental health research, neurology, cancer, and psychiatry.